heuristic_models

Python

#Load library and data

import pandas as pd

from ChannelAttributionPro import *

Data = pd.read_csv("https://app.channelattribution.io/data/Data.csv",sep=";")

#Set your token

token="yourtoken"

#Perform transaction level attribution from a data.frame

path_attribution=heuristic_models(Data=Data, var_path="path", var_conv="total_conversions", 
                                  var_value="total_conversion_value", cha_sep=">")
print(path_attribution)

#Return non converting paths in the output data.frame

path_attribution=heuristic_models(Data=Data, var_path="path", var_conv="total_conversions", 
                                  var_value="total_conversion_value", cha_sep=">", 
                                  flg_write_nulls=1)
print(path_attribution)

#Return paths in the output data.frame

path_attribution=heuristic_models(Data=Data, var_path="path", var_conv="total_conversions", 
                                  var_value="total_conversion_value", cha_sep=">", 
                                  flg_write_paths=1)
print(path_attribution)


#Perform transaction level attribution from a file and write output to file

import requests
response = requests.get("https://app.channelattribution.io/data/Data.csv")
with open("Data.csv", "wb") as f:
    f.write(response.content)

res=heuristic_models(Data="Data.csv", var_path="path", var_conv="total_conversions", 
                     var_value="total_conversion_value", cha_sep=">", row_sep=";", 
                     file_output="ouput.csv")
print(res)